{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "7683b36a",
   "metadata": {},
   "source": [
    "# tiktoken (OpenAI) Length Function\n",
    "You can also use tiktoken, a open source tokenizer package from OpenAI to estimate tokens used. Will probably be more accurate for their models.\n",
    "\n",
    "1. How the text is split: by character passed in\n",
    "2. How the chunk size is measured: by `tiktoken` tokenizer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "1ad2d0f2",
   "metadata": {},
   "outputs": [],
   "source": [
    "# This is a long document we can split up.\n",
    "with open('../../../state_of_the_union.txt') as f:\n",
    "    state_of_the_union = f.read()\n",
    "from langchain.text_splitter import CharacterTextSplitter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "825f7c0a",
   "metadata": {},
   "outputs": [],
   "source": [
    "text_splitter = CharacterTextSplitter.from_tiktoken_encoder(chunk_size=100, chunk_overlap=0)\n",
    "texts = text_splitter.split_text(state_of_the_union)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "ae35d165",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Madam Speaker, Madam Vice President, our First Lady and Second Gentleman. Members of Congress and the Cabinet. Justices of the Supreme Court. My fellow Americans.  \n",
      "\n",
      "Last year COVID-19 kept us apart. This year we are finally together again. \n",
      "\n",
      "Tonight, we meet as Democrats Republicans and Independents. But most importantly as Americans. \n",
      "\n",
      "With a duty to one another to the American people to the Constitution.\n"
     ]
    }
   ],
   "source": [
    "print(texts[0])"
   ]
  }
 ],
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